This paper describes the Shape Optimization of Switched Reluctance Machine (SRM) using Genetic Algorithm (GA). To achieve the required performance within a specified space envelope, the physical dimensions of the Switched Reluctance Machine like Stator pole arc, Rotor pole arc, Rotor diameter and Stack length were optimized using GA. The proposed strategy improves the Power Density by 13.97 % using GA. The maximum Torque throughput is enhanced by 12.1 %. The proposed design, in comparison with the standard design, highlights improvement in performance with considerable reduction in size. This method maximizes Flux linkage and Torque per unit rotor volume of the SRM. In this paper, the design specifications are suited for 25hp, 24/18 pole, 4 phase SRM. The simulation results obtained from the given specifications, demonstrate the efficacy of the proposed strategy.

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-A major problem in Switched Reluctance Motor (SRM) is torque ripple, which causes undesirable acoustic noise and vibration. This work focuses on reducing the undesirable torque ripple in SRM by modifying stator and rotor geometry. This paper presents a comparative study on torque ripple minimization in SRM with modified pole shapes such as stator pole taper, stator pole face with non-uniform air gap and pole shoe attached to rotor pole. Further this paper presents a detailed sensitivity analysis of the effect of different geometrical parameters that alter the pole face shapes on the performance of SRM. The analysis is performed using finite-element method considering average torque and torque ripple as performance parameters. Based on the analysis, a design combining stator pole taper with non-uniform air gap is proposed to improve the torque characteristics of SRM. The dynamic characteristics of the proposed design are simulated and the results show satisfactory reduction in torque ripple.